Instance Segmentation on TBBR

Metric: Average Recall@IoU:0.5-0.95 (higher is better)

LeaderboardDataset

Results

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#	Model↕	Average Recall@IoU:0.5-0.95▼	Extra Data	Paper	Date↕	Code
1	Swin-T (ImageNet-1k pretrain)	28	No	-	-	Code
2	Mask R-CNN (ResNet-50-FPN, ImageNet-1k pretrain)	21.9	No	-	-	Code
3	Swin-T	20.6	No	-	-	Code
4	Mask R-CNN (ResNet-50-FPN)	20.1	No	-	-	Code
5	Wahn Mask R-CNN	9.4	No	-	-	-

#1Swin-T (ImageNet-1k pretrain)
28
Average Recall@IoU:0.5-0.95
No paperCode
#2Mask R-CNN (ResNet-50-FPN, ImageNet-1k pretrain)
21.9
Average Recall@IoU:0.5-0.95
No paperCode
#3Swin-T
20.6
Average Recall@IoU:0.5-0.95
No paperCode
#4Mask R-CNN (ResNet-50-FPN)
20.1
Average Recall@IoU:0.5-0.95
No paperCode
#5Wahn Mask R-CNN
9.4
Average Recall@IoU:0.5-0.95
No paper